GitLab

* python-package: refine plot_tree

This change splits plot_tree to two methods:
1. method of creating digraph of tree
2. method of plotting the digraph with matplotlib

* fix doc

* fix doc

* many refactors.

* remove multi_loglossova.

* fix tests.

* avoid using lambda function.

* fix some format.

* reduce branching.

* Update Python-API.md

* for a better jump in page

A space is needed between `#` and the headers content according to Github's markdown format [guideline](https://guides.github.com/features/mastering-markdown/)

After adding the spaces, we can jump to the exact position in page by click the link.

* fixed something mentioned by @wxchan

* Update Python-API.md

* add data_splitter for cv

* update gitignore

* clean code

* refine plot

* use warnings

* refine  logic

* revert 'move to compat.py'

* Support Poisson regression

Close #233

* update docs

* add plot metrics

* move 'raise Exception' to check_not_tuple_of_2_elements

* rename 'plot_metrics' to 'plot_metric'

* fix misleading message/docs

* change 'Metrics' in title to 'Metric'

* fix misleading comment

* add plot tree

* add docs

* add example

* add test

* fix test

* fix decision type

* add show_info

* use feature name if available

* add plot importance

* add plot example

* suppprt pandas categorical

* refine logic

* make default=auto

* fix train/valid categorical codes

* add test

* unify set _predictor

* fix tests

* fix warning

* support feature_name=int

http://research.microsoft.com/en-us/um/people/zhang/INRIA/Publis/Tutorial-Estim/node24.html

* Add L1 objective function

* fix hessians

* update

* Add Huber loss

https://en.wikipedia.org/wiki/Huber_loss

* update

* update docs/Parameters.md

* update

* use handle is not None for _is_constructed

* sort imports; clean code; move FAQ to docs

* add @property to sklearn interface

* add deprecated; fix binary_metric

* fix creating valid_sets

* support both list and dict

* update Python-API.md

* remove other parameters in sklearn fit

* add dart parameters to sklearn init